An X-ray CT apparatus is an apparatus which emits X-rays from the periphery of an object, collects data regarding the intensity of X-rays transmitted through the object using an X-ray detector, and forms distribution information of an X-ray absorption coefficient inside the object as an image on the basis of the collected data.
The image reconstruction method is roughly divided into an analytical reconstruction method and an algebraic reconstruction method. Examples of the analytical reconstruction method of the image reconstruction method include a Fourier transform method, a filtered back projection method, and a convolution integral method, and examples of the algebraic reconstruction method include an iterative reconstruction method represented by an MLEM (Maximum Likelihood Expectation Maximization) method or an OSEM (Ordered Subset Expectation Maximization) method. Among these, when the analytical method that is currently commercialized is applied to a multi-slice CT with a wide cone angle (angle of an X-ray beam spreading in a slice direction), there is a problem in that cone beam artifacts are generated due to imperfections in the reconstruction algorithm. On the other hand, the algebraic reconstruction method is known to have high perfection compared with the analytical reconstruction method, while the computation time is long since the operation is performed recursively. For this reason, the algebraic reconstruction method has conventionally been used in the field of nuclear medical imagery, but is not popular in the field of X-ray CT imagery. However, the problem of the computation time in the algebraic reconstruction method (iterative reconstruction method) is being solved by the development of computer technology in recent years. PTL 1 discloses using an iterative reconstruction method for image formation of an X-ray CT apparatus to improve the image quality.
PTL 1 discloses a technique of suppressing the amount of computation while improving the image quality of a region of interest by setting the matrix size of the region of interest to be different from the matrix sizes of other regions and reconstructing an image using an iterative method.
In addition, PTL 2 discloses a technique of suppressing degradation of image quality in a region of interest, which is caused by degradation of image quality outside the region of interest, by sampling the region densely when a region where high resolution is required is present outside the region of interest.
In addition, PTL 2 discloses a technique of suppressing the amount of computation by increasing the convergence in the iterative method by estimating the convergence for each pixel and updating pixels selectively, which are to be updated, in an image.